TY - JOUR
T1 - Toward Dexterous Manipulation with Augmented Adaptive Synergies
T2 - The Pisa/IIT SoftHand 2
AU - Santina, Cosimo Della
AU - Piazza, Cristina
AU - Grioli, Giorgio
AU - Catalano, Manuel G.
AU - Bicchi, Antonio
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2018/10
Y1 - 2018/10
N2 - In recent years, a clear trend toward simplification emerged in the development of robotic hands. The use of soft robotic approaches has been a useful tool in this prospective, enabling complexity reduction by embodying part of grasping intelligence in the hand mechanical structure. Several hand prototypes designed according to such principles have accomplished good results in terms of grasping simplicity, robustness, and reliability. Among them, the Pisa/IIT SoftHand demonstrated the feasibility of a large variety of grasping tasks, by means of only one actuator and an opportunely designed tendon-driven differential mechanism. However, the use of a single degree of actuation prevents the execution of more complex tasks, like fine preshaping of fingers and in-hand manipulation. While possible in theory, simply doubling the Pisa/IIT SoftHand actuation system has several disadvantages, e.g., in terms of space and mechanical complexity. To overcome these limitations, we propose a novel design framework for tendon-driven mechanisms, in which the main idea is to turn transmission friction from a disturbance into a design tool. In this way, the degrees of actuation (DoAs) can be doubled with little additional complexity. By leveraging on this idea, we design a novel robotic hand, the Pisa/IIT SoftHand 2. We present here its design, modeling, control, and experimental validation. The hand demonstrates that by opportunely combining only two DoAs with hand softness, a large variety of grasping and manipulation tasks can be performed, only relying on the intelligence embodied in the mechanism. Examples include rotating objects with different shapes, opening a jar, and pouring coffee from a glass.
AB - In recent years, a clear trend toward simplification emerged in the development of robotic hands. The use of soft robotic approaches has been a useful tool in this prospective, enabling complexity reduction by embodying part of grasping intelligence in the hand mechanical structure. Several hand prototypes designed according to such principles have accomplished good results in terms of grasping simplicity, robustness, and reliability. Among them, the Pisa/IIT SoftHand demonstrated the feasibility of a large variety of grasping tasks, by means of only one actuator and an opportunely designed tendon-driven differential mechanism. However, the use of a single degree of actuation prevents the execution of more complex tasks, like fine preshaping of fingers and in-hand manipulation. While possible in theory, simply doubling the Pisa/IIT SoftHand actuation system has several disadvantages, e.g., in terms of space and mechanical complexity. To overcome these limitations, we propose a novel design framework for tendon-driven mechanisms, in which the main idea is to turn transmission friction from a disturbance into a design tool. In this way, the degrees of actuation (DoAs) can be doubled with little additional complexity. By leveraging on this idea, we design a novel robotic hand, the Pisa/IIT SoftHand 2. We present here its design, modeling, control, and experimental validation. The hand demonstrates that by opportunely combining only two DoAs with hand softness, a large variety of grasping and manipulation tasks can be performed, only relying on the intelligence embodied in the mechanism. Examples include rotating objects with different shapes, opening a jar, and pouring coffee from a glass.
KW - Biologically inspired robots
KW - dexterous manipulation
KW - mechanism design
KW - multifingered hands
KW - underactuated robots
UR - http://www.scopus.com/inward/record.url?scp=85048149631&partnerID=8YFLogxK
U2 - 10.1109/TRO.2018.2830407
DO - 10.1109/TRO.2018.2830407
M3 - Article
AN - SCOPUS:85048149631
SN - 1552-3098
VL - 34
SP - 1141
EP - 1156
JO - IEEE Transactions on Robotics
JF - IEEE Transactions on Robotics
IS - 5
M1 - 8373731
ER -